Why has decentralized storage always been overlooked? Simply put, it's two words—slow. Data read latency is outrageously high, social applications require instant rendering, and game resource calls need millisecond responses. In these scenarios, decentralized storage is practically a nightmare. But Walrus has changed this situation, achieving millisecond-level data reading and breaking the long-standing performance ceiling in the industry.

The secret lies in the innovation of the coding scheme. Traditional erasure codes use complex polynomial calculations to restore data, resulting in lengthy decoding processes. Walrus adopts RedStuff 2D coding, replacing it with XOR operations, which are much simpler logically, leading to a significant increase in decoding speed. Even more clever is its slicing design, allowing data to be reconstructed without downloading the full copy—retrieving only partial primary slices and secondary slices is enough. This trick can significantly reduce transmission time.

Having good coding alone isn't enough; the network architecture must also keep pace. Walrus employs a layered strategy: edge nodes are deployed close to users to store popular data for high-frequency access; core nodes store cold data behind the scenes, responsible for long-term security. When users read data, they fetch directly from the nearest edge node, completely avoiding cross-region connections, which greatly reduces network latency.

With this combination, decentralized storage finally sheds the label of "cold backup tool" and begins to support real-time application scenarios.